<group>
<ul class='breadcrumb'><li><a href='%pathto:mdoc;'>Index</a></li><li><a href='%pathto:vl_harris;'>Prev</a></li><li><a href='%pathto:vl_noprefix;'>Next</a></li></ul><div class="documentation"><p>
The VLFeat MATLAB toolbox provides implementations of common
computer vision algorithms (SIFT, MSER, AIB, KMEANS, ...) and
other useful MATLAB functions, some of which are listed next:
</p><ul><li><p>
<a href="%pathto:sift.vl_sift;">VL_SIFT</a>() computes the Scale-Invariant Feature Transform.  SIFT
bundels the most widely used feature detector and
descriptor. This version is compatbile with Lowe's original
implementation.
</p></li><li><p>
<a href="%pathto:mser.vl_mser;">VL_MSER</a>() computes the Maximally-Stable Extremal Regions of an
image. It detects features corresponding to stable image level
sets.
</p></li><li><p>
<a href="%pathto:kmeans.vl_ikmeans;">VL_IKMEANS</a>() and <a href="%pathto:kmeans.vl_hikmeans;">VL_HIKMEANS</a>() are basic implementations of K-means
and hierarchical IKM optimized to work on integer data
types. This is useful to quantize large collection of features,
for instance to create visual dictionaries.
</p></li><li><p>
<a href="%pathto:aib.vl_aib;">VL_AIB</a>() uses the AIB algorithm to discriminatively compress a
discrete random variable. An application is the compresssion
of a visual dictionary for categorization.
</p></li><li><p>
<a href="%pathto:imop.vl_imarray;">VL_IMARRAY</a>() and <a href="%pathto:imop.vl_imarraysc;">VL_IMARRAYSC</a>() tile image stacks, <a href="%pathto:imop.vl_imsc;">VL_IMSC</a>()
scales the range of an image, <a href="%pathto:imop.vl_imsmooth;">VL_IMSMOOTH</a>() convolves an image
by a number of different kernels, <a href="%pathto:imop.vl_imwbackward;">VL_IMWBACKWARD</a>() warps an
image by backward mapping, <a href="%pathto:imop.vl_waffine;">VL_WAFFINE</a>(), <a href="%pathto:imop.vl_wtps;">VL_WTPS</a>(), <a href="%pathto:imop.vl_witps;">VL_WITPS</a>()
compute various kind of image warps, <a href="%pathto:imop.vl_imwhiten;">VL_IMWHITEN</a>() whitens an
image, <a href="%pathto:imop.vl_xyz2lab;">VL_XYZ2LAB</a>(), <a href="%pathto:imop.vl_xyz2luv;">VL_XYZ2LUV</a>(), <a href="%pathto:imop.vl_xyz2rgb;">VL_XYZ2RGB</a>(), <a href="%pathto:imop.vl_rgb2xyz;">VL_RGB2XYZ</a>()
perform basic color space conversions.
</p></li><li><p>
<a href="%pathto:plotop.vl_cf;">VL_CF</a>() to copies a figure, <a href="%pathto:plotop.vl_tightsubplot;">VL_TIGHTSUBPLOT</a>() provides a
&quot;borderless&quot; version of SUBPLOT(), <a href="%pathto:plotop.vl_click;">VL_CLICK</a>() and
<a href="%pathto:plotop.vl_clickpoint;">VL_CLICKPOINT</a>() interactively select image points,
<a href="%pathto:plotop.vl_printsize;">VL_PRINTSIZE</a>() scales a figure printing size to a fraction of
the default paper size, <a href="%pathto:plotop.vl_plotframe;">VL_PLOTFRAME</a>() to plot feature frames
(points, disks, oriented disks, ellipses, oriented ellpises).
</p></li><li><p>
<a href="%pathto:misc.vl_binsum;">VL_BINSUM</a>() computeds binned summations (and compute
histograms), <a href="%pathto:misc.vl_twister;">VL_TWISTER</a>() controls and runs VLFeat internal
random number generator (useful to reproduce results from
randomized algorithms), <a href="%pathto:misc.vl_whistc;">VL_WHISTC</a>() computes weighed histograms,
<a href="%pathto:misc.vl_grad;">VL_GRAD</a>() computes the gradient of a 2-D function.
</p></li></ul><p>
See also: http://www.vlfeat.org.
</p></div></group>
